Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and non-pathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the entire meat production chain. Here, a metagenomics approach and shotgun sequencing technology was used as a tool to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica, Listeria monocytogenes, generic Escherichia coli, Staphylococcus aureus, Clostridium (C. botulinum, C. perfringens), and Campylobacter (C.jejuni, C.coli, C.fetus), decreased over subsequential processing steps. Furthermore, normalized read counts for Salmonella enterica, Escherichia coli, and Clostridium botulinum were greater in the final product, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome, but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach-one of the main challenges was in the identifying the specific pathogen to which the sequence reads originated, which makes this approach unpractical to be used for pathogen identification for regulatory and confirmation purposes.

BibTex

@article{Yang12022016,
author = {Yang, Xiang and Noyes, Noelle R. and Doster, Enrique and Martin, Jennifer N. and Linke, Lyndsey M. and Magnuson, Roberta J. and Yang, Hua and Geornaras, Ifigenia and Woerner, Dale and Jones, Kenneth L. and Ruiz, Jaime and Boucher, Christina and Morley, Paul S. and Belk, Keith E.},
title = {Use of metagenomic shotgun sequencing technology to detect foodborne pathogens within their microbiome in beef production chain},
year = {2016},
doi = {10.1128/AEM.00078-16},
abstract ={Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and non-pathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the entire meat production chain. Here, a metagenomics approach and shotgun sequencing technology was used as a tool to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica, Listeria monocytogenes, generic Escherichia coli, Staphylococcus aureus, Clostridium (C. botulinum, C. perfringens), and Campylobacter (C. jejuni, C. coli, C. fetus), decreased over subsequential processing steps. Furthermore, normalized read counts for Salmonella enterica, Escherichia coli, and Clostridium botulinum were greater in the final product, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome, but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach—one of the main challenges was in the identifying the specific pathogen to which the sequence reads originated, which makes this approach unpractical to be used for pathogen identification for regulatory and confirmation purposes.},
URL = {http://aem.asm.org/content/early/2016/02/08/AEM.00078-16.abstract},
eprint = {http://aem.asm.org/content/early/2016/02/08/AEM.00078-16.full.pdf+html},
journal = {Applied and Environmental Microbiology}
}